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United States Department of Agriculture

Agricultural Research Service

Research Project: IMPROVING GENETIC PREDICTIONS FOR DAIRY ANIMALS USING PHENOTYPIC AND GENOMIC INFORMATION Title: Incidence validation and relationship analysis of producer-recorded health event data from on-farm computer systems in the United States

Authors
item Parker Gaddis, K -
item Cole, John
item Clay, J -
item Maltecca, C -

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 24, 2012
Publication Date: September 1, 2012
Citation: Parker Gaddis, K.L., Cole, J.B., Clay, J.S., Maltecca, C. 2012. Incidence validation and relationship analysis of producer-recorded health event data from on-farm computer systems in the United States. Journal of Dairy Science. 95(9):5422-5435.

Interpretive Summary: Substantial progress has been made in the genetic improvement of production traits while health and fitness traits of dairy cattle have declined. Data collected from on-farm computer management systems may provide an effective and low-cost source of health information. The current study sought to examine the credibility of producer-recorded health data throughout the U.S. on a large scale. Once credibility was established, causal relationships were examined between diseases. The results provide evidence that producer-recorded data sufficiently represent the true incidence of health events.

Technical Abstract: The principal objective of this study was to analyze the credibility of health data recorded through on-farm recording systems throughout the US and the relationships between health events on a large scale. Substantial progress has been made in the genetic improvement of production traits while health and fitness traits of dairy cattle have declined. Health traits are generally expensive and difficult to measure, but health event data collected from on-farm computer management systems may provide an effective and low-cost source of health information. In order to validate editing methods, incidence rates of on-farm recorded health event data were compared to incidence rates reported in literature. Putative causal relationships among common health events were examined using logistic regression for each of three timeframes: 0 to 60, 61 to 90, and 91 to 150 days in milk. Health events occurring on average before the health event of interest were included in each model as predictors when significant. Calculated incidence rates ranged from 1.37% for respiratory problems to 12.32% for mastitis. Most health events reported had incidence rates lower than the average incidence rate found in literature. This may partially represent under-reporting by dairy farmers who record disease events only when a treatment or other intervention is required. Path diagrams developed using odds ratios calculated from logistic regression models for each of 13 common health events allowed putative relationships to be examined. The greatest odds ratios were estimated to be the influence of ketosis on displaced abomasum (15.5) and the influence of retained placenta on metritis (8.37), and were consistent with earlier reports. The results of this analysis provide evidence for the credibility of on-farm recorded health information.

Last Modified: 10/22/2014
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